Smartphones have become a standard utensil in the vast majority of everyone’s daily life. Importantly, it has become rather customary to employ smartphones when having to navigate within novel environments. In fact, Navigation Assistance Systems (NAS) are used extensively by pedestrians and vehicle operators alike. While this technological revolution provides a remarkable tool for everyday spatial exploration, there has been a growing body of work focusing on the impact of NAS upon perception and interaction with the environment. More specifically, Wunderlich and colleagues aim at investigating the impact of NAS on the neurophysiological mechanisms underpinning spatial cognition in general and incidental spatial learning in particular.
The interest of the Berlin Mobile Brain/Body Imaging Lab (BeMoBIL) to further explore the impact of NAS on spatial cognition was driven by prior studies suggesting that excessive use of NAS technology leads to a decrease of orienting abilities (Münzer, Zimmer, Schwalm, Baus, & Aslan, 2006). In fact, several studies have shown that the use of visual-based NAS interferes with visuo-motor spatial processing during navigation (resulting in an automation bias) due to the increase in attentional demands (e.g . Lin, Kuehl, Schöning, & Hecht, 2017). Ultimately, this results in the over-reliance on the NAS by the user in order to cope with the increased cognitive demands and, consequently, to diminished spatial processing (Fenech, Drews, & Bakdash, 2010).
Interestingly, auditory-based NAS seem to be beneficial for spatial navigation, and to interfere less with visuo-motor processes (May & Ross, 2006; Wunderlich & Gramann, 2018). Further, Gramann and colleagues (2017) showed that auditory navigation instructions could improve incidental spatial learning when landmarks were augmented in a virtual driving task (Gramann, Hoepner, & Karrer-Gauss, 2017, Wunderlich & Gramann, 2018). Here, Wunderlich and Gramann investigated how auditory NAS instructions affect spatial navigation and subsequent spatial memory trace retrieval within real-world settings.